A memetic algorithm to maximise the employee substitutability in personnel shift scheduling

Abstract

Personnel rosters are typically constructed for a medium- term period under the assumption of a deterministic operating environment. However, organisations usually operate in a stochastic environment and are confronted with unexpected events in the short term. These unexpected events affect the workability of the personnel roster and need to be resolved efficiently and effectively. To facilitate this short-term recovery, it is important to consider robustness by adopting proactive scheduling strategies during the roster construction. In this paper, we discuss a proactive strategy that maximises the employee substitutability value in a personnel shift scheduling context. We propose a problem-specific population-based approach with local and evolutionary search heuristics to solve the resulting non-linear personnel shift scheduling problem and obtain a medium-term personnel shift roster with a maximised employee substitutability value. Detailed computational experiments are presented to validate the design of our heuristic procedure and the selection of the heuristic operators.